Exogenous Methyl Jasmonate Application Improved Physio-Biochemical Attributes, Yield, Quality, and Cadmium Tolerance in Fragrant Rice.

Cadmium (Cd) has detrimental effects on crop plants, whereas, jasmonates (JAs) play a vital role in abiotic stress tolerance in plants. The present study investigated the effects of exogenous application of methyl jasmonate (MeJa) on the physio-biochemical attributes, yield, and quality of two fragrant rice cultivars, i.e., Xiangyaxiangzhan and Meixiangzhan-2 under Cd stress. The experiment was comprised of four treatments, i.e., CK, control (normal conditions); Cd: 100 mg Cd kg-1 of soil; MeJa: exogenous application of MeJa at 20 mM; and Cd + MeJa: 100 mg Cd kg-1 of soil + exogenous MeJa application at 20 mM. Results depicted that Cd toxicity resulted in a substantial reduction of enzymatic activities and non-enzymatic antioxidants, chlorophyll contents, while enhanced oxidative damage in the terms of lipid peroxidation (higher malondialdehyde (MDA) contents), H2O2, and electrolyte leakage. Proline contents were found higher whereas protein and soluble sugars were lower under Cd stress as compared with Ck and Cd + MeJa. Exogenous MeJa application further improved the panicles per pot, spikelets per panicle, seed setting (%), 1,000 grain weight, and yield per pot under Cd stress conditions as compared with non-MeJa applied plant under Cd stress. In addition, exogenous MeJa application enhanced the accumulation of macro (N, P, K, Mg, and Ca) and micronutrients (Mn, Zn, Fe, and Cr) in both cultivars under Cd stress, while reduced the Cd contents in different plant parts. Overall, the contents of Cd in different plant organs were recorded as: root > stem > leaves > grains for all treatments. Comparing both cultivars, the grain Cd contents were higher in Meixiangzhan 2 than Xiangyaxianzhan under Cd contaminated conditions. Conclusively, Cd toxicity impaired growth in rice by affecting physio-biochemical attributes, however, Xiangyaxiangzhan performed better than Meixiangzhan-2 cultivar.

Estimating reed loss caused by Locusta migratoria manilensis using UAV-based hyperspectral data.

Locusta migratoria manilensis has caused major damage to vegetation and crops. Quantitative evaluation studies of vegetation loss estimation from locust damage have seldom been found in traditional satellite-remote-sensing-based research due to insufficient temporal-spatial resolution available from most current satellite-based observations. We used remote sensing data acquired from an unmanned aerial vehicle (UAV) over a simulated Locusta migratoria manilensis damage experiment on a reed (Phragmites australis) canopy in Kenli District, China during July 2017. The experiment was conducted on 72 reed plots, and included three damage duration treatments with each treatment including six locust density levels. To establish the appropriate loss estimation models after locust damage, a hyperspectral imager was mounted on a UAV to collect reed canopy spectra. Loss components of six vegetation indices (RVI, NDVI, SAVI, MSAVI, GNDVI, and IPVI) and two "red edge" parameters (Dr and SDr) were used for constructing the loss estimation models. Results showed that: (1) Among the six selected vegetation indices, loss components of NDVI, MSAVI, and GNDVI were more sensitive to the variation of dry weight loss of reed green leaves and produced smaller estimation errors during the model test process, with RMSEs ranging from 8.8 to 9.1 g/m;. (2) Corresponding model test results based on loss components of the two selected red edge parameters yielded RMSEs of 27.5 g/m2 and 26.1 g/m2 for Dr and SDr respectively, suggesting an inferior performance of red edge parameters compared with vegetation indices for reed loss estimation. These results demonstrate the great potential of UAV-based loss estimation models for evaluating and quantifying degree of locust damage in an efficient and quantitative manner. The methodology has promise for being transferred to satellite remote sensing data in the future for better monitoring of locust damage of larger geographical areas.

Mapping deforestation and urban expansion in Freetown, Sierra Leone, from pre- to post-war economic recovery.

Freetown, the capital of Sierra Leone has experienced vast land-cover changes over the past three decades. In Sierra Leone, however, availability of updated land-cover data is still a problem even for environmental managers. This study was therefore, conducted to provide up-to-date land-cover data for Freetown. Multi-temporal Landsat data at 1986, 2001, and 2015 were obtained, and a maximum likelihood supervised classification was employed. Eight land-cover classes or categories were recognized as follows: water, wetland, built-up, dense forest, sparse forest, grassland, barren, and mangrove. Land-cover changes were mapped via post-classification change detection. The persistence, gain, and loss of each land-cover class, and selected land conversions were also quantified. An overall classification accuracy of 87.3 % and a Kappa statistic of 0.85 were obtained for the 2015 map. From 1986 to 2015, water, built-up, grassland, and barren had net gains, whereas forests, wetlands, and mangrove had net loses. Conversion analyses among forests, grassland, and built-up show that built-up had targeted grassland and avoided forests. This study also revealed that, the overall land-cover change at 2001-2015 was higher (28.5 %) than that recorded at 1986-2001 (20.9 %). This is attributable to the population increase in Freetown and the high economic growth and infrastructural development recorded countrywide after the civil war. In view of the rapid land-cover change and its associated environmental impacts, this study recommends the enactment of policies that would strike a balance between urbanization and environmental sustainability in Freetown.

Mineral resources prospecting by synthetic application of TM/ETM+, Quickbird and Hyperion data in the Hatu area, West Junggar, Xinjiang, China.

The Hatu area, West Junggar, Xinjiang, China, is situated at a potential gold-copper mineralization zone in association with quartz veins and small granitic intrusions. In order to identify the alteration zones and mineralization occurrences in this area, the Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM+), Quickbird, Hyperion data and laboratory measured spectra were combined in identifying structures, alteration zones, quartz veins and small intrusions. The hue-saturation-intensity (HSI) color model transformation was applied to transform principal component analysis (PCA) combinations from R (Red), G (Green) and B (Blue) to HSI space to enhance faults. To wipe out the interference of the noise, a method, integrating Crosta technique and anomaly-overlaying selection, was proposed and implemented. Both Jet Propulsion Laboratory Spectral Library spectra and laboratory-measured spectra, combining with matched filtering method, were used to process Hyperion data. In addition, high-resolution Quickbird data were used for unraveling the quartz veins and small intrusions along the alteration zones. The Baobei fault and a SW-NE-oriented alteration zone were identified for the first time. This study eventually led to the discovery of four weak gold-copper mineralized locations through ground inspection and brought new geological knowledge of the region's metallogeny.